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on Labor Markets - Supply, Demand, and Wages |
| By: | Andrew Johnston; Christos A. Makridis |
| Abstract: | Does artificial intelligence (AI) increase productivity - and does it displace workers? We examine aggregate effects using administrative data covering essentially all U.S. employers in a difference-in-differences design exploiting occupational AI exposure across industries and states. A one standard deviation increase in exposure raises output by 7%, with effects emerging in 2021 when enterprise AI tools entered the market. Employment effects follow the same timing but diverge by exposure type: where AI likely requires human collaboration, employment rises 4%; where AI can perform tasks independently, we find no significant employment effect. Results are robust to state-by-year and industry-by-year fixed effects and suggest AI has caused a decrease in the labor share of income. |
| Keywords: | artificial intelligence, generative AI, aggregate productivity, labor market, technological change |
| JEL: | O33 J24 J23 E24 O47 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12579 |
| By: | David H. Autor; Caroline Chin; Anna Salomons; Bryan Seegmiller |
| Abstract: | We study the role of expertise in new work - novel occupational roles that emerge as technological and economic conditions evolve - using newly available 1940 and 1950 Census Complete Count files and confidential American Community Survey data from 2011-2023. We show that new work is systematically distinct from simply more work in existing occupations in four respects. First, it attracts workers with distinct characteristics: new work is disproportionately performed by younger and more educated workers, even within detailed occupation-industry cells. Second, new work commands economically significant wage premiums that persist beyond workers' initial entry into new work, consistent with returns to scarce, specialized expertise rather than temporary market disequilibrium. Third, these premiums decline across vintages as expertise diffuses, with `newer' new work commanding larger premiums than older new work. Fourth, the emergence of new work can be traced to specific demand shocks in particular locations and time periods, suggesting that expertise formation responds systematically to economic opportunities. These findings suggest that new work serves as a countervailing force to automation-driven job displacement not merely by creating additional employment, but also by generating new domains of human expertise that command market premiums. This expertise-based mechanism helps explain both the expanding variety of work activities across decades and the historical resilience of the labor share. |
| Keywords: | new work, technological change, occupations, tasks |
| JEL: | E24 J11 J23 J24 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12577 |
| By: | Yana Gallen; Juanna Schrøter Joensen; Eva Rye Johansen; Gregory F. Veramendi; Juanna Schrøter Joensen |
| Abstract: | We study the labor market impact of unplanned pregnancy among women using long-acting reversible contraceptives to delay pregnancy. While most women successfully delay, some have unplanned pregnancies, providing quasi-random variation in pregnancy timing. Analyzing linked health and labor market data from Sweden, we find that unplanned pregnancies halt women's career progression, resulting in income losses of 19% five years later. We find similar effects of unplanned births among women using short-acting reversible contraceptives. Using pregnancy as an instrument for birth in a dynamic treatment effect framework, effects of unplanned children are more detrimental for younger women and those enrolled in education. |
| Keywords: | labor market costs of motherhood, fertility, contraceptives, unplanned pregnancy |
| JEL: | J13 J22 J24 J31 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12586 |
| By: | Bernhard, Sarah (IAB Nürnberg); Bohmann, Sandra (DIW Berlin); Fiedler, Susann (WU Wien); Kasy, Maximilian; Schupp, Jürgen (DIW Berlin); Schwerter, Frederik (Frankfurt School of Finance and Management) |
| Abstract: | How does basic income (a regular, unconditional, guaranteed cash transfer) impact labor supply? We show that in search models of the labor market with income effects, this impact is theoretically ambiguous: Employment and job durations might increase or decrease, match surplus might be shifted to workers or employers, and worker surplus might be reallocated between wages and job amenities. We thus turn to empirical evidence to study this impact. We conducted a pre-registered RCT in Germany, starting 2021, where recipients received 1200 Euro/month for three years. We draw on both administrative and survey data, and find no extensive margin (employment) response, and no impact on on job transitions from either non-employment or employment. We do find a small statistically insignificant intensive margin shift to parttime employment, which implies an excess burden (reduction of government revenues) of ca 7.5% of the transfer. We furthermore observe a small increase of enrolment in training or education. |
| Keywords: | BASIC INCOME, RANDOMIZED CONTROLLED TRIAL, LABOR SUPPLY |
| JEL: | I38 J22 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:amz:wpaper:2026-08 |
| By: | Noriaki Matsushima (Osaka School of International Public Policy, the University of Osaka); Kazuki Nishikawa (Graduate School of Economics, the University of Osaka); Jiaying Qiu (Graduate School of Economics, the University of Osaka) |
| Abstract: | A binding minimum wage can raise the regulated firm's profits when labor-market power interacts with product-market competition. We develop a duopoly model in which firms compete in the same product market but hire workers from distinct, geographically segmented labor markets. Because the minimum wage applies only to one firm's labor market, it does not directly raise its rival's costs. With monopsony power, the minimum wage reduces the regulated firm's marginal cost and induces it to expand output, forcing its rival to contract through strategic interaction. Under Cournot competition, this mechanism also increases total employment and consumer surplus. |
| Keywords: | Minimum wage, Monopsony power, Segmented labor markets, Product-market competition |
| JEL: | J38 J42 L13 J23 C72 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:osp:wpaper:26e003 |
| By: | Drydakis, Nick (Anglia Ruskin University) |
| Abstract: | This study examines whether AI Capital, defined as AI-related knowledge, skills and capabilities, is associated with business innovation among SMEs in England. Using a two-wave longitudinal panel dataset comprising 504 observations from SMEs collected in 2024 and 2025, the study develops and validates a 45-item AI Capital of Business scale. Business innovation is measured across five dimensions: product and service innovation, process innovation, technology adoption, market and customer engagement, and organisational culture and strategy. Regression models, including pooled OLS, Random Effects, and Fixed Effects specifications, are employed. The findings reveal a robust positive association between AI Capital and business innovation across all model specifications. This association holds across all business innovation dimensions and remains consistent for SMEs with differing levels of financial performance, size, and operational maturity. Each component of AI Capital independently exhibits a positive association with business innovation outcomes. |
| Keywords: | artificial intelligence, artificial intelligence capital, business innovation, innovation, SMEs |
| JEL: | O31 O33 O32 L26 L25 M15 D83 J24 O14 O39 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18476 |
| By: | Yoshimichi Murakami (Research Institute for Economics & Business Administration, Kobe University, JAPAN); Aya Noritake (Graduate School of Economics, Kobe University, JAPAN) |
| Abstract: | Although the defined contribution pension system in Chile had not permitted pension withdrawals before retirement age, the Chilean Congress approved laws allowing early withdrawals as an economic support measure in response to the COVID-19 pandemic. This study empirically analysed the effects of mainly the third early pension withdrawal on pre-retirement labour supply using data from a nationally and regionally representative household survey for 2022. To address potential endogeneity from self-selection into pension withdrawals, we applied inverse probability weighting based on propensity score estimation. The results showed that individuals who withdrew their pensions worked longer hours and had a higher probability of employment. These effects were more pronounced among women, while they were statistically insignificant for men. The findings were robust to household-level analysis, which additionally showed that pension savings withdrawn by women were more likely to be used for home repairs. Therefore, the early pension withdrawal, rather than reducing labour supply through the income effect, encouraged female labour supply, possibly due to improved remote-work conditions. |
| Keywords: | Early pension withdrawal; Labour supply; Chile; Inverse probability weighting; Propensity score; COVID-19 |
| JEL: | H55 J22 J26 J32 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:kob:dpaper:dp2026-10 |
| By: | Mallory Avery; Edwin Ip; Andreas Leibbrandt; Joseph Vecci |
| Abstract: | Recent technological advancements are reshaping pathways to employment by automating the interview process. Asynchronous interviews, in which job applicants submit answers to interview questions via an online platform without interacting with an interviewer, are replacing more traditional face-to-face job interviews. At the same time, AI algorithms are now widely used to assess these interview answers. In this paper, we use a field experiment to comprehensively study how these new technologies affect applicants and employers in the recruitment process. Over 3, 000 job applicants are randomized into asynchronous audio or video interviews, live online interviews, and a control group. Their job interviews are then assessed by both professional recruiters and a commercial AI recruitment tool used by most Fortune 100 companies. We find that asynchronous interviews cause an over 50% decrease in application continuation, including among the most qualified applicants, and that this decline is largest for women. A complementary vignette experiment provides evidence that this deterrence is driven by perceptions about the competitiveness and fairness of the recruitment process. In terms of assessments, we find that the AI evaluation tool scores women and underrepresented racial minorities higher than human evaluators, while the opposite is true for men, Whites and Asians. We track our applicants' subsequent labor market outcomes and find that the AI assessment tool predicts subsequent employment success substantially better than human recruiters, suggesting that AI captures soft skills and potential that humans overlook. In addition, we provide evidence that, unlike AI, human recruiters' assessments suffer from multiple cognitive biases. Our findings provide some of the first key evidence on how recent technological advances are transforming the hiring process. |
| Keywords: | technological change, artificial intelligence, gender, field experiment |
| JEL: | C93 J23 J71 J78 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12573 |
| By: | Frisancho, Veronica (CAF - Development Bank of Latin America and the Caribbean, Buenos Aires, Argentina); Gallegos, Sebastian (Universidad Adolfo Ibañez); Gonzalez, Constanza (Universidad Adolfo Ibañez) |
| Abstract: | Do second chances at a high-stakes admission exam yield long-term gains? Leveraging fifteen years of Chilean administrative data and an RDD, we examine the causal effects of retaking on educational and labor market trajectories. Narrowly missing a preferred program cutoff triggers a 44% increase in retaking, leading to substantial score gains (0.27 SD) and improved placement and enrollment chances. However, these immediate gains do not persist. Retakers graduate at the same rate and from programs with similar earnings and employability profiles as their counterfactual peers. Our results suggest that retaking serves as a reshuffling mechanism yielding null net welfare gains. |
| Keywords: | high-stakes exams, college admissions, exam retaking, regression discontinuity, Chile, educational trajectories, labor market outcomes, centralized admission systems |
| JEL: | I23 I24 I28 J24 J62 N36 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18467 |
| By: | Bernd Irlenbusch (University of Cologne & London School of Economics and Political Science); Holger A. Rau (University of Duisburg-Essen & University of Gottingen); Rainer Michael Rilke (WHU – Otto Beisheim School of Management) |
| Abstract: | LLMs are rapidly entering the hiring process, but their most pronounced effects may occur before any screening by changing who chooses to apply. We study how human versus LLM-based evaluation and gender transparency shape entry into competitive jobs. In a preregistered online experiment, participants first complete a Niederle and Vesterlund (2007) tournament task to measure competitive preferences, then prepare text-based job applications and decide whether to apply under each of four evaluation regimes—human only, LLM only, and two hybrid human-in-the-loop configurations—while gender disclosure is randomized between subjects. LLM involvement reduces application rates, with stronger effects for women than men, including under hybrid designs. Effects are driven by non-competitive candidates; non-competitive women, the group most exposed to AI-induced deterrence, receive the strongest objective evaluations under pure AI assessment across all subgroups, yet are systematically underconfident and apply least often. Competitive men persistently apply and exhibit overconfidence-driven adverse selection, whereas competitive women show resilience to AI-induced deterrence while remaining well-calibrated under AI evaluation and exhibiting positive self-selection across regimes. We find no effects of gender transparency. |
| Keywords: | AI hiring, LLMs, algorithm aversion, gender differences |
| JEL: | C92 J71 J24 O33 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:ajk:ajkdps:398 |
| By: | St'Anna, Pedro (Massachusetts Institute of Technology); Sardoschau, Sulin (Humboldt University Berlin); Schmeisser, Aiko (Columbia University) |
| Abstract: | Empirical studies of racial wage disparities typically rely on self-reported race and treat racial categories as fixed. This paper shows that racial classification in the labor market is produced by social perception, and that modeling this process is essential for measuring wage gaps. We combine two large administrative data sets to construct three racial identity measures for 330, 000 workers in Brazil (2003-2015): employer classification, self-identification, and an algorithmic skin-tone measure. Self-identified and employer-ascribed race differ in over 20 percent of cases, and employers disagree about the same worker. We estimate a "race function" describing how employers map phenotypic cues, self-identification, education, and employment histories into racial categories. Holding skin tone constant, university graduates are substantially more likely to be perceived as White. Measured wage gaps vary across racial definitions, and accounting for perception meaningfully alters disparity estimates. We show that conventional approaches overstate the role of productivity differences in explaining racial wage gaps. |
| Keywords: | Race, identity, disparity, wage gap, Brazil |
| JEL: | J15 J50 J71 Z10 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18473 |
| By: | Serdar Birinci; Loukas Karabarbounis; Kurt See |
| Abstract: | In the 1990s, Americans used to work much more than non-Americans. Nowadays, about half of the gap in hours worked has reversed. To evaluate the convergence of working hours, we develop a tractable model of labor supply enriched with multiple sources of heterogeneity across individuals, an extensive margin of participation, multi-member households, and an elaborate system of taxes and benefits upon non-employment. Using detailed measurements from micro-level and aggregate datasets, we identify model parameters and sources of heterogeneity across individuals for various countries. We run a horse race between competing explanations and find that U.S. hours per person declined after 2000 owing mainly to the rise of government health benefits provided to the non-employed. Non-U.S. countries have generous benefits for the non-employed, but this generosity has not changed as much overtime as in the United States, and public health coverage does not depend on employment status or income levels. For these countries, the rise of labor supply is generally accounted for by a mix of factors, such as the rise of wages and the falling disutility of work. |
| Keywords: | employment; hours; wages; benefits |
| JEL: | E24 E60 H53 J22 |
| Date: | 2026–03–24 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedlwp:102929 |
| By: | Tomasz Sulka (HU Berlin) |
| Abstract: | This paper develops a dynamic search model in which certain ``hidden attributes" are revealed only after acceptance of an offer and may trigger continued search in the following period. The model is applied to study how workers' imperfect information about pecuniary workplace benefits (such as employer-sponsored pension and health insurance plans) during job search, and the subsequent realization of these benefits on the job, affect the multidimensional compensation packages offered in equilibrium by profit-maximizing firms. I find that unobservability of benefits prior to acceptance distorts firms' incentives toward providing inefficiently low benefits, despite the fact that lower benefits induce higher worker turnover. Furthermore, when workers differ in strategic sophistication, and therefore hold different beliefs about unobservable benefits, there exist equilibria with spurious differentiation in compensation packages. In these equilibria, the wage differential is bounded from above by the benefit differential. The model demonstrates how imperfect information about workplace benefits can explain several empirical puzzles, including inefficiently low benefit provision and large between-firm dispersion in benefits. |
| Keywords: | exploitative contracting; hidden attributes; job search; workplace benefits; compensating differentials; |
| JEL: | D83 D91 J31 J32 J33 |
| Date: | 2026–03–23 |
| URL: | https://d.repec.org/n?u=RePEc:rco:dpaper:566 |
| By: | Arellano-Bover, Jaime (Yale University); Bussotti, Carolina (Rome Economics Doctorate); Paradisi, Matteo (EIEF); Wu, Liangjie (EIEF) |
| Abstract: | Brand capital--an intangible asset that differentiates a firm's products--has grown in recent decades, alongside the rise of intangible investment and the decline in the labor share. Trademarks are legal claims on brand capital and are traded across firms, providing a setting to study how reallocating brand capital reshapes firm behavior and aggregate outcomes. Leveraging a novel link of Italian administrative data on trademark ownership, firms' financial statements, and employer–employee records, we exploit firm-to-firm trademark transactions to identify the effects of brand-capital investment. Guided by a model in which firms combine production and expansionary with brand capital, we use an event-study design to estimate firm-level and aggregate effects. Acquiring a trademark increases intangible assets by 19%, sales by 8%, and employment by 6%, while leaving weekly earnings unchanged and reducing the firm-level labor share. Employment gains are concentrated among marketing and sales workers. Trademark transactions reallocate brand capital toward larger firms, raising combined buyer-seller sales. Calibrating the model, we find this reallocation generates a one percentage-point long-run decline in the aggregate labor share. |
| Keywords: | brand capital, trademarks, labor share, labor demand, markups |
| JEL: | L25 O34 E25 J23 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18461 |
| By: | Alexander Bick; Adam Blandin; David J. Deming; Nicola Fuchs-Schündeln; Jonas Jessen; David Deming |
| Abstract: | This paper combines international evidence from worker and firm surveys conducted in 2025 and 2026 to document large gaps in AI adoption, both between the US and Europe and across European countries. Cross-country differences in worker demographics and firm composition account for an important share of these gaps. AI adoption, within and across countries, is also closely linked to firm personnel management practices and whether firms actively encourage AI use by workers. Micro-level evidence suggests that AI generates meaningful time savings for many workers. At the macro level, in recent years industries with higher AI adoption rates have experienced faster productivity growth. While we do not establish causality, this relationship is statistically significant and similar in magnitude in Europe and the US. We do not find clear evidence that industry-level AI adoption is associated with employment changes. We discuss limitations of existing data and outline priorities for future data collection to better assess the productivity and labor market effects of AI. |
| Keywords: | generative AI, technology adoption, labor productivity |
| JEL: | J24 M16 O14 O33 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12584 |
| By: | Stephanie Coffey; Joshua S. Goodman; Amy Ellen Schwartz; Leanna Stiefel; Marcus A. Winters; Yunee H. Yoon |
| Abstract: | Special education serves more than one in seven U.S. students yet its causal impact remains understudied. Using longitudinal data from Massachusetts, Indiana, and Connecticut, we estimate the effect of individualized supports with an event-study design that tracks achievement around initial classification. Students' scores decline prior to placement and rise sharply afterward, yielding a consistent V-shaped pattern. Within three years, achievement is 0.2–0.4σ higher than counterfactual trends imply. Gains are similar across disability categories and subgroups, are not driven by testing accommodations, and remain under conservative assumptions. Individualized supports substantially increase learning productivity. |
| Keywords: | special education, disability, achievement, pre-trends |
| JEL: | I21 I28 H52 J24 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12587 |
| By: | Pulito, Giuseppe (ROCKWOOL Foundation Berlin); Pytlikova, Mariola (CERGE-EI, Charles University and the Economics Institute of the Czech Academy of Sciences, and AIAS, Aarhus University); Schroede, Sarah (Aarhus University and Ratio Institute); Lodefalk, Magnus (Örebro University School of Business) |
| Abstract: | Using two waves of nationally representative Danish firm surveys linked to employer– employee administrative registers, we study how adoption varies across artificial intelligence (AI) and related advanced technologies. We show that AI adoption is highly technologyspecific. While firm size and digital infrastructure predict adoption broadly, workforce composition operates through distinct channels: STEM-educated workforces predict core AI adoption, whereas non-STEM university-educated workforces are associated with generative AI adoption, indicating different human capital complementarities. The factors associated with adoption differ from those predicting deployment breadth: firm size and digital maturity matter for both, whereas workforce composition primarily predicts adoption alone. Machine learning and natural language processing are deployed across multiple business functions, whereas other advanced technologies remain concentrated in specific operational domains. Individual-level evidence provides a foundation for these patterns, with awareness of workplace AI usage concentrated among managers and high-skilled workers. Self-reported AI knowledge is higher among younger and more educated individuals. Finally, commonly used occupational AI exposure measures vary substantially in their ability to predict observed adoption, with benchmark-based measures outperforming patent-based and LLM-focused alternatives. These findings show that treating AI as a monolithic category obscures economically meaningful variation in who adopts, what they deploy, and how well existing measures capture it. |
| Keywords: | Artificial Intelligence; Technology Adoption; Digitalisation; Human capital; AI Exposure Measures. |
| JEL: | D24 J23 J62 O33 |
| Date: | 2026–03–27 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:oruesi:2026_003 |
| By: | David Hummels; Jakob Munch; Huilin Zhang |
| Abstract: | We build a model of CEO compensation that unites principal-agent and assignment models in the face of trade shocks that interact with CEO effort. The model predicts that trade shocks change CEO compensation through scale, volatility, and ability-magnification channels. Using Danish matched worker-firm data, we find empirical support for these channels: (1) Exogenous shocks to trade increase the size and value of the firm and CEO compensation; (2) the share of firm value paid to the CEO is increasing in the size and value of the firm and increasing in the volatility induced by global shocks; (3) Higher-ability CEOs generate increases in firm value that are more than 100 times greater than their compensation, through a combination of mitigating losses and maximizing the return to positive shocks. |
| JEL: | F16 G30 J30 J31 M52 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35004 |
| By: | Mayara Felix |
| Abstract: | I estimate the effect of trade on local labor market concentration and its implications for wages using employer-employee linked data and tariff shocks from Brazil’s trade liberalization. Trade increased concentration by 7%, an effect driven by firm exit and worker flows to surviving import-competing firms. Increased concentration reduced wage take-home shares—estimated at 50 cents on the dollar pre-shock—enough to offset small wage gains from reallocation, but did not meaningfully reduce wages on net. Most of the wage declines attributed to Brazil's trade liberalization resulted instead from reductions in the marginal revenue product of labor. Incorporating informality reveals substantial regional heterogeneity. |
| JEL: | F16 O1 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35018 |
| By: | Daas, Yousuf; Dalmon, Danilo Leite |
| Abstract: | South Africa entered the COVID-19 pandemic with one of the world's most unequal labor markets, where racial stratification shaped not only employment access but the distribution of wages within employment. This paper estimates the differential effect of the post-2020 period on monthly wages using seven waves of the Labor Market Dynamics in South Africa (LMDSA) dataset spanning 2017 to 2023. The empirical strategy employs a difference-in-differences design with race-by-post-2020 interaction terms, conditional on province, year-by-quarter, education, industry, and occupation fixed effects, with standard errors clustered at the survey stratum level. The results show that racial wage inequality widened sharply and persistently after 2020 across all subgroups examined. Among wage employees, African/Black workers experienced a relative wage penalty of approximately 37 percent and Colored workers approximately 52 percent. The most striking finding concerns employers: African/Black business owners suffered a relative earnings loss of approximately 59 percent, entirely reversing a modest pre-pandemic advantage, exposing the fragility of post-apartheid entrepreneurial gains. Gender-disaggregated estimates reveal larger conditional penalties for non-White men than women among the employed, though this coexists with documented severe labor force exclusion of women during the crisis. Occupational strata analysis confirms that penalties are present across all skill levels and are not explained by compositional sorting across industries or occupations. These findings are consistent with a structural amplifier interpretation, whereby the pandemic revealed and entrenched pre-existing vulnerabilities in a segmented labor market rather than generating new ones. |
| Date: | 2026–03–20 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:8xrjc_v1 |
| By: | Wensu Li; Atin Aboutorabi; Harry Lyu; Kaizhi Qian; Martin Fleming; Brian C. Goehring; Neil Thompson |
| Abstract: | This paper develops a unified framework for evaluating the optimal degree of task automation. Moving beyond binary automate-or-not assessments, we model automation intensity as a continuous choice in which firms minimize costs by selecting an AI accuracy level, from no automation through partial human-AI collaboration to full automation. On the supply side, we estimate an AI production function via scaling-law experiments linking performance to data, compute, and model size. Because AI systems exhibit predictable but diminishing returns to these inputs, the cost of higher accuracy is convex: good performance may be inexpensive, but near-perfect accuracy is disproportionately costly. Full automation is therefore often not cost-minimizing; partial automation, where firms retain human workers for residual tasks, frequently emerges as the equilibrium. On the demand side, we introduce an entropy-based measure of task complexity that maps model accuracy into a labor substitution ratio, quantifying human labor displacement at each accuracy level. We calibrate the framework with O*NET task data, a survey of 3, 778 domain experts, and GPT-4o-derived task decompositions, implementing it in computer vision. Task complexity shapes substitution: low-complexity tasks see high substitution, while high-complexity tasks favor limited partial automation. Scale of deployment is a key determinant: AI-as-a-Service and AI agents spread fixed costs across users, sharply expanding economically viable tasks. At the firm level, cost-effective automation captures approximately 11% of computer-vision-exposed labor compensation; under economy-wide deployment, this share rises sharply. Since other AI systems exhibit similar scaling-law economics, our mechanisms extend beyond computer vision, reinforcing that partial automation is often the economically rational long-run outcome, not merely a transitional phase. |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2603.29121 |
| By: | Goulas, Sofoklis (foundry10 & Yale University) |
| Abstract: | This study documents a new fact about educational production: Students’ relative standing in noncognitive skills has lasting effects distinct from absolute skills and achievement. Using administrative data from Greece and quasi-random classroom assignment, I identify the causal impact of comparative noncognitive skills, measured as grade 10 classroom rank in grade 9 unexcused absences. A worse rank has persistent, nonlinear effects. While it lowers achievement for both genders, boys respond by sorting into more competitive tracks and higher-earning degrees, whereas girls shift toward less competitive paths. Gender differences in comparative noncognitive skills explain 37% of the gap in expected post-college salaries. Complementary evidence from a survey experiment shows that comparative behavioral labels systematically shift teachers’ expectations and attribution patterns for otherwise identical students. This suggests that relative-standing effects operate through belief-driven institutional responses. |
| Keywords: | noncognitive skills, ordinal rank, peer effects, STEM, gender gap |
| JEL: | I21 I24 J24 J16 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18471 |
| By: | Donna K. Ginther; Joshua L. Rosenbloom |
| Abstract: | This chapter examines the dramatic growth and evolving role of postdoctoral researchers in the U.S. scientific workforce from 1979 to 2023, highlighting a fourfold increase in postdoc numbers that outpaced growth in graduate students and faculty. We argue that this expansion reflects the fragmented nature of science funding, particularly the effects of the NIH budget doubling in the early 2000s, which increased both supply and demand for postdocs but ultimately worsened employment conditions. The chapter also explores the career outcomes of postdocs, noting limited economic returns outside academia and declining transitions to faculty roles. With recent declines in postdoc numbers, tightening immigration policies, and rising compensation, it seems likely that the U.S. may have reached “peak postdoc, ” potentially leading to reduced future research output. The chapter concludes with a call for improved data and further research to better understand postdocs’ roles in scientific production and career development. |
| JEL: | I23 J40 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35014 |
| By: | Han, Luyi (Pennsylvania State University); Winters, John (Iowa State University); Betz, Michael (The Ohio State University) |
| Abstract: | The 21st century fracking boom transformed American energy production, but new jobs were often filled by temporary in-migrants and long-distance commuters, possibly reducing economic benefits for prior residents. We use novel restricted-access data from the U.S. Census Bureau to assess fracking impacts on prior residents. We examine impacts on earnings and employment for persons born in non-metropolitan fracking counties. We utilize an event study design to estimate annual impacts during the fracking boom, drilling downturn, and subsequent periods. We find sizable impacts on average log earnings that peaked during the boom and partially persisted during and after the downturn. The fracking boom also increased the probability of being employed but the effect largely disappeared after fracking activity peaked. We also compare our main result for non-metropolitan natives to persons born in metropolitan counties and conduct several other extensions. |
| Keywords: | fracking, local labor markets, resource boom, rural development |
| JEL: | Q4 R2 J3 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18466 |
| By: | Emanuele Forlani (University of Pavia); Concetta Mendolicchio (University of Genova); Agnese Sechi (University of Genova) |
| Abstract: | This paper investigates the gendered effects of trade liberalization on local labor markets in Italy, a country marked by low female labor force participation. Building on recent evidence that trade shocks can exacerbate or mitigate gender inequalities depending on labor market segmentation and institutional context, we examine how exposure to Chinese and Eastern European import competition has affected the labor market in Italy, with a focus on the gender discrepancies. We construct a shift-share measure of import exposure, exploiting variation in pre-existing industry specialization across provinces. Using labor-force survey and trade data with detailed labor market indicators, we assess whether observed gender gaps result from asymmetric dynamics between women and men, and how these patterns vary by sector, contract type, and skills. By providing new empirical evidence and a theoretical framework to interpret these patterns, our findings indicate that trade shocks tend to reinforce existing gender disparities in Italy, with effects concentrated in sectors characterized by high female employment shares and precarious job arrangements. |
| Keywords: | Import competition, labour market, gender inequality |
| JEL: | F14 J21 J16 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:pav:demwpp:demwp0233 |
| By: | Ueno, Yuko (Hitotsubashi University); Usui, Emiko (Hitotsubashi University) |
| Abstract: | This study investigates gender differences in labor market outcomes among highly educated individuals in Japan, emphasizing heterogeneity by fields of study, with a focus on STEM. Using data from the Japanese Panel Study of Employment Dynamics (JPSED), we find that women with STEM degrees begin their careers with earnings comparable to men with at least a bachelor’s degree in any field; yet the gap widens to 24.4 percent six to ten years after graduation. Penalties are especially large for mothers and remain sizable for childless women. Field differences are stark: six to ten years out, women with STEM bachelor’s degrees, Social Sciences, or Humanities degrees earn less than men with high-school or junior-college education. In contrast, women with STEM advanced degrees or Medicine/Pharmacy degrees earn more than men with a high-school or junior-college education, and women with Medicine/Pharmacy degrees maintain wage parity with men holding at least a bachelor’s degree in any field. These findings indicate that family responsibilities matter, but structural barriers against women also contribute to persistent gender gaps, with holders of advanced degrees in STEM, Medicine, or Pharmacy as notable exceptions. |
| Keywords: | STEM, field of study, female, Japan |
| JEL: | J16 J24 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18465 |
| By: | Markiewicz, Zuzanna (University of Warwick) |
| Abstract: | This study examines whether the 2013 FAA First Officer Qualifications (1, 500-hour) rule reshaped competitive dynamics across U.S. legacy and regional carriers, measured by group-level mean changes in offered seat capacity relative to Mexican and Canadian carriers outside the rule’s jurisdiction. Triple-Difference and Difference-in-Differences models are estimated on an airport-pair–carrier–month–year-level data on passenger flights on bidirectional U.S.–Canada and U.S.–Mexico routes market from 2012 to 2014. On average, post-policy, the U.S. legacy–regional capacity gap in offered seats widened by 46% relative to the corresponding foreign legacy–regional gap. U.S. regional carriers reduced offered seats by 19% relative to foreign regional carriers, while U.S. legacy carriers increased offered seats by 34% relative to foreign legacy carriers. Overall, the safety-oriented tightening of pilot-qualification requirements appears to have produced unintended competitive spillovers with asymmetric effects, consistent with wage-sensitive U.S. regional airlines curtailing operations and larger-scale U.S. legacy carriers gaining market power. |
| Keywords: | 1, 500-hour rule ; pilot qualification requirements ; labour supply constraints ; airline competition ; regulatory asymmetry JEL classifications: L93 ; L51 ; L13 ; J44 ; R48 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:wrkesp:97 |
| By: | Sutirtha Bagchi (Department of Economics, Villanova School of Business, Villanova University) |
| Abstract: | The 2018 Supreme Court decision in Janus v. AFSCME eliminated mandatory union fees for public-sector workers, overturning four decades of legal precedent. Using administrative payroll data from 400 jurisdictions across 21 states, I find that dues-paying membership declined by 8.9 to 13.4 percent by 2021, a drop substantially smaller than anticipated. At least three-quarters of this decline reflects the automatic termination of agency fees rather than voluntary exits by union members. Teachers, police, and firefighters maintained relatively stable membership, while support staff experienced declines of 13 to 18 percent. Despite these membership losses, I find no impact on overall earnings. |
| Keywords: | Public-sector unions; Union membership; Collective bargaining; Agency fees; Janus; Freeriding |
| JEL: | J45 H75 K31 J51 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:vil:papers:63 |
| By: | Claudia Curi; Andreas Dibiasi; Matteo Ploner; Mirco Tonin |
| Abstract: | We study whether gender-biased financial advice contributes to the gender gap in pension wealth. Using administrative records from four private pension funds in Italy, we document that women are ceteris paribus 8 percentage points less likely than men to choose stock-focused investment lines at the time of enrollment. To assess whether advisory behavior contributes to this gap, we conduct a vignette-based survey experiment among pension advisors affiliated to the four funds, randomly varying the gender of otherwise identical prospective 25-year-old clients. Advisors are 22 percentage points less likely to recommend stock-oriented portfolios to female clients, even after conditioning on advisors' beliefs about relevant client characteristics. We further show that a simple information intervention that makes advisors aware of the documented gender bias eliminates this gap in the experimental setting. Linking advisors to real clients in the administrative data, we demonstrate that the gender gap in actual investment choices shrinks by approximately 60% during the five months following the intervention. This evidence suggests that gender bias in financial advice is largely implicit and that low-cost informational feedback to advisors can meaningfully reduce gender disparities in retirement wealth accumulation. |
| Keywords: | biased advice, gender, pension, implicit bias |
| JEL: | J16 G53 J32 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12569 |
| By: | Patrick Illien; Olayinka Aremu; Ben Jann; Eva-Marie Meemken |
| Abstract: | -Background- The world is facing a severe drug crisis, posing serious public health and societal risks. Yet, little is known about drug use among farmers and farmworkers, key contributors to global food production. Poor mental health and precarious working conditions in agriculture are common. Farmers and workers may turn to drugs to cope with these conditions, however, evidence on drug use in agriculture is extremely limited. A challenge in collecting such data is social desirability bias stemming from the topic's sensitivity. We address this gap by using sensitive question techniques and offer novel evidence on drug use among farmers and farmworkers, highlighting links between working conditions, work-related health, and drug consumption. -Methods- We conducted item-count and item-sum double list experiments with 1, 554 farmers and workers to measure the prevalence and frequency of drug use in Nigeria's labour-intensive tomato sector where the topic is highly relevant. List experiments avoid direct questioning and can estimate sensitive behaviours, while hiding respondents' answers from the interviewer. Using these estimates, we ran multivariate regressions to identify work-related risk factors of drug use, focusing on burnout, work-related pain and health problems, pesticide exposure, unusual working hours, and belief in work performance effects. -Results- The item-count experiment suggests that about 8% of farmers, 20% of seasonal workers, and 6% of casual workers used drugs in the previous 12 months. The item-sum experiment finds that drug-using farmers and seasonal workers have consumed drugs on about 8 days in the last month on average (farmers possibly more than that), and drug-using casual workers on 7 days. Multivariate regressions show that work-related pain and belief in performance-enhancing effects are the most important risk factors for frequent drug use. Our results also demonstrate that burnout levels are significantly higher among farmworkers than among farmers, but we do not find a significant association between work-related burnout and drug use. -Conclusions- Farmers and farmworkers suffer from important occupational health deficits. Drug use and mental health in rural areas in particular remain underappreciated on policy and research agendas. Implications for agricultural productivity and rural development should be further explored. |
| Keywords: | drug use, burnout, working conditions, occupational health, farmwork, agricultural employment, list experiment, sensitive question technique, Nigeria |
| JEL: | C83 C99 I12 J43 J81 O13 |
| Date: | 2026–04–01 |
| URL: | https://d.repec.org/n?u=RePEc:bss:wpaper:62 |
| By: | Kumar Gautam, Santosh (University of Notre Dame); Shandal, Monica (University of California, Santa Cruz); Zucker, Ariel (University of California, Santa Cruz) |
| Abstract: | We examine the impact of rural road connectivity on economic and novel governance outcomes in the context of the world’s largest rural road program, India’s PMGSY. Using a novel village-level survey designed around PMGSY’s rollout, we exploit quasi-random variation in road placement to estimate causal effects of connectivity on agricultural and labor markets as well as governance and political connectivity. We find evidence that roads support market access, as local producer prices increase by 1.3 SD and agricultural outputs diversify. Despite the improved agricultural output prices and options, labor shifts away from agriculture to casual work, suggesting improved non-agricultural market access. Interestingly, increases in casual labor are almost exclusively local to the connected village, and we find a decrease of short- and medium-term migration by 0.8 SD. Additionally, road connectivity increases local state presence, with a 1.1 SD increase in an index of official government visits and a 0.9 SD increase in an index of political connectivity, and leads to higher wages on government construction projects and lower prices in government shops. Our findings show that road leads to more vibrant and diverse rural economies. |
| Keywords: | infrastructure, governance, PMGSY, labor markets, migration, India |
| JEL: | J43 O12 O18 R23 R42 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18468 |
| By: | Priyanka Anand; Tamar Matiashvili; Maya Rossin-Slater |
| Abstract: | Paid leave policies are designed to help workers balance work with caregiving responsibilities, yet research has focused predominantly on parental leave while the literature on non-parental caregiving leave remains nascent. This chapter reviews the evidence on the impacts of paid family leave (PFL) and paid sick leave (PSL) policies, with a focus on non-childbirth-related caregiving. We begin with an overview of the prevalence and challenges of informal caregiving in the US and internationally, followed by a description of the current paid caregiving leave policy landscape. We then review evidence on the impact of these policies on leave take-up, labor market outcomes, caregiver health and well-being, employer outcomes, and utilization of formal care. We find that paid leave policies have successfully increased leave take-up and that PFL improves labor market outcomes for workers with caregiving responsibilities, without adversely affecting employers. There is also some suggestive evidence of improvements in caregivers’ mental health. We additionally provide an update of the paid parental leave literature since it was last reviewed by Rossin-Slater (2018), describing the latest evidence on maternal health, child health and development, parental labor market outcomes, and employer outcomes. We conclude by identifying key gaps in the literature, including the lack of research on the outcomes of (non-child) care recipients, limited evidence on employer responses, and the underexplored role of PSL in supporting caregiving needs. |
| JEL: | I18 J13 J14 J38 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34997 |
| By: | Lucia Torres Frasele (Health Economics, Policy and Innovation Institute, Faculty of Economics and Administration, Masaryk University, Brno, Czech Republic) |
| Abstract: | This paper examines the causal effects of Menopause Hormone Therapy (MHT) on health and labor market outcomes among U.S. women aged 40–61. I leverage the MHT treatment arm of the first large-scale randomized evaluation of MHT’s effects on postmenopausal women’s health, which was stopped early due to elevated health risks and publicly announced in July 2002. The announcement led to a rapid global decline in MHT prescriptions, which I use as a quasi-exogenous shock. Using nationally representative U.S. data on prescriptions, health, and labor market outcomes, I apply difference-in-differences, instrumental variables, and fixed-effects approaches. Results show MHT significantly improves physical health, increasing physical functioning scores by up to one standard deviation, but effects on employment and wages are modest and sensitive to specification. |
| Keywords: | women’s health; menopause; aging; employment |
| JEL: | I12 J14 J16 J21 J22 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:mub:wpaper:2026-01 |